AI Engineer

The posting, as Tessera Labs wrote it

ABOUT TESSERA LABS

Tessera Labs is a new category of enterprise software: an AI platform that changes how the world's largest companies run.

Every large enterprise carries the same weight — decades of accumulated process, data, and code that no longer match the business it has become. Changing any of it is a program measured in years and hundreds of millions of dollars, staffed by armies of consultants, and it fails more often than anyone admits. Most companies have quietly accepted this as the cost of being large.

We don't. Tessera is a transformation engine: a governed, multi-agent platform that understands an enterprise's process, data, and code as one connected system and changes it in weeks rather than years. We're vendor-agnostic by design — SAP, Salesforce, Workday, Oracle, Snowflake, MuleSoft — and tied to none of them.

Two things make this hard, and they're the reason the job is interesting. Governance: every action is logged, traceable, and reversible, because our customers are regulated and these are the systems that close their books. And generality: the platform has to work on landscapes it has never seen, at companies whose complexity is genuinely unique to them.

We sell a product, not a service. Our people are here to make the product successful, not the other way around. If you've watched enterprise AI companies quietly become consultancies, that distinction is the one to press us on.

We raised a $60M Series A led by Andreessen Horowitz, with Foundation Capital, Myriad Venture Partners, and Osage University Partners participating.

ABOUT THE ROLE

Turning platform capability into outcomes a Fortune 500 will bet on has two halves — the systems that surround the model, and the model itself. This role owns the first.

You will own agents end to end: the harness they run in, the tools they call, the context they see, the guardrails around them, and the evals that tell us whether any of it is improving. Most of the difficulty is not model access. It's an agent reasoning across a landscape with nineteen years of undocumented decisions embedded in it, where one call silently returns a stale schema forty steps into a plan — and the work of making that failure legible, reproducible, and then impossible.

This is not a prototyping role. Everything you build gets pointed at systems a company's quarter close depends on.

If the model itself interests you more than the systems around it, look at Research Engineer — same team, other half of the problem.

WHAT YOU'LL DO

• Design and ship the production agents that do transformation work: understanding a landscape, planning a change, executing it across process, data, and code, and proving it was correct.
• Build the tool layer — typed, permissioned, well-documented interfaces that let agents read and act across enterprise systems without ever exceeding what a human approver authorized.
• Improve agent performance through prompting, context construction, tool-use strategy,

[…]
engineering, model evaluation — and reach for it when it beats a prompt.

• Treat evaluation as engineering rather than a report you generate at the end.
• Think in systems and customer outcomes, not model metrics.
• Are comfortable with non-determinism and have opinions about building reliably on top of it.
• Write strong Python and are comfortable in TypeScript.
• Ship fast, and verify before you claim it works.
• Find large, ugly, undocumented enterprise systems interesting rather than beneath you. That instinct is most of the job, and it's rarer than it should be.

STRONG CANDIDATES MAY ALSO HAVE

• Hands-on experience with enterprise platforms, their APIs, and their extension models — SAP, Salesforce, Workday, Oracle, Snowflake, MuleSoft, ServiceNow.
• Experience with knowledge graphs, ontologies, or semantic models over messy real-world systems.
• Experience with code analysis, program transformation, or automated refactoring at scale.
• Experience with MCP, sub-agents, or agent skill/plugin architectures.
• A background in distributed systems or workflow engines, where partial failure is the default case.
• Experience at an early-stage startup or as a founder, where scope was whatever needed doing that week.
• Familiarity with enterprise security and compliance realities: SSO, RBAC, segregation of duties, PII handling, SOC 2, data residency.

JOIN THE FUTURE OF AI AT TESSERA LABS

We're looking for someone who enjoys building reliable, scalable systems that help teams move faster. If you take pride in cutting-edge AI, value clear ownership, and want to have a meaningful impact in a fast-moving environment, you’ll fit right in.

No third party may recruit, solicit candidates, publish job opportunities, use Tessera Labs’ name or branding, or represent that they are acting on behalf of Tessera Labs without prior written authorization. Any such activity conducted without explicit written consent is strictly prohibited.